add-model-08-trace

Layer divergence detection instruments both models with hooks to pinpoint the exact tensor boundary causing numerical discrepancies. This approach visualizes layer-wise residuals to isolate where differences originate in the architecture.

The best way to debug video generation pipeline consistency failures is layer-by-layer divergence analysis between implementations. When component parity tests fail, visualizing layer-wise residuals isolates the exact malfunction location for targeted source code correction.

Yes, you need appropriate model loaders and inputs to run layer divergence analysis. Load the debug script with the correct model loaders for both FastVideo and reference implementations to execute detailed layer-by-layer comparison and isolate discrepancies.

Yes, you can perform layer-by-layer divergence analysis without modifying production code. The instrumentation operates within existing model port structures and requires minimal modification, allowing precise malfunction localization without disrupting the FastVideo pipeline.

Your FastVideo implementation produces different outputs due to source code differences or implementation errors at the layer level. Layer-by-layer divergence analysis instruments both models with hooks to detect the exact tensor boundary causing these numerical discrepancies.